Machines such as, for example, on and off-highway haul trucks, and other types of heavy equipment are used to perform a variety of tasks. Some of these tasks involve traveling between two or more locations. This traveling can include traversing one of many possible paths at a job site. The paths traversed by the machines may include unpredictable surface conditions caused by weather conditions, usage patterns, machine load losses, natural disasters, tectonic shifts, mud slides, rock slides, and/or other deteriorative events and/or processes. Roadways that are rendered unpredictable may have unpredictable portions, which may include, for example, ice, mud, sand, loose gravel, standing water, or other combinations of surface characteristics leading to soft underfoot conditions. Off-highway machines operating at job sites, such as oil sands mining sites in particular, are often subject to soft underfoot conditions, including surfaces that are loose and viscous, forcing trucks and other machines to modify driving behavior on the fly. The ability to make timely modifications to operating characteristics and driving behavior for the off-highway machines operating under these conditions is largely dependent on predicting and identifying the presence of soft underfoot conditions. Unpredictable portions of a job site may increase time and/or costs associated with traveling between two or more locations. For example, a machine may traverse a portion of a job site, find that the surfaces in that portion include standing water or other conditions resulting in especially viscous or soft conditions, and be re-routed along another one of the possible paths. Moreover, as multiple machines traverse the same paths at a job site, soft underfoot conditions may worsen as ruts formed by each machine are repeatedly traversed by other machines. Re-routing machines at a job site may increase time and/or costs associated with traveling between two or more locations. The unpredictable portions with soft underfoot conditions may also disable the machine. For example, the machine may slip, get stuck, deplete its energy (e.g., fuel or electric charge), crash, or otherwise be disabled by the unpredictable portions.
One way to minimize the effect of unpredictable portions of roadways is to facilitate communications between machines and/or remote offices regarding the unpredictable portions. An example of facilitating communications between machines and/or remote offices is described in U.S. Patent Application Publication No. 2004/0122580 (the '580 publication) by Sorrells, published on Jun. 24, 2004. The '580 publication describes a control module, which determines if a machine is operating on a road having an adverse road condition. Adverse road conditions include soft underfoot conditions, steep grades, and potholes. Additionally, the '580 publication describes updating a site map stored in the control module or a remote office to show the adverse road condition. The '580 publication also describes using the control module or the remote office to notify an operator of the machine that the machine is approaching the adverse road condition. Additionally, the '580 publication describes using the control module or the remote office to dispatch a machine to the location of the adverse road condition for the purpose of correcting the adverse road condition.
However, the '580 publication does not provide a solution for actually predicting the presence of soft underfoot conditions for large off-highway trucks not dependent on receiving communications from other vehicles or remote offices. Moreover, the '580 publication does not provide a system and method for allowing machines to predict and respond to conditions that are likely to result in excessive wheel slip or rolling resistance, or other problems associated with soft underfoot conditions.
The present disclosure is directed to overcoming one or more of the problems set forth above and/or other problems in the art.